Numbers of controls and cases

disease_class n percent
control 155 46.69%
infected 177 53.31%

Differential Gene Expression

comparison up up % down down % mean count cutoff low counts low counts %
infected vs control 2058 4.66 % 3348 7.58 % 0 14562 32.96 %
Note:
44183 with nonzero total read count
Outliers: 0

25 genes with largest negative log-fold change in experimental group

infected_vs_control: downregulated in infected
gene log2FoldChange lfc standard error pvalue* padj
AC090227.1 12.0 3.30 0.0e+00 1.3e-17
MTCO1P40 6.3 0.99 0.0e+00 2.3e-15
AC005258.1 4.0 0.70 2.0e-07 5.9e-06
MTND1P23 3.4 0.68 0.0e+00 1.2e-08
AL355916.3 3.2 0.47 0.0e+00 1.6e-09
AC004057.1 2.7 0.47 0.0e+00 1.1e-07
AC006238.2 2.7 0.71 8.9e-03 0.049
RPL29P11 2.5 0.76 1.0e-07 4.2e-06
CR848007.2 2.3 0.52 1.0e-04 0.0014
AC093765.2 2.1 0.30 0.0e+00 1.6e-11
LINC02088 2.1 0.69 7.7e-03 0.044
MTCO1P12 2.1 0.69 2.8e-06 6.3e-05
AC093843.2 2.0 0.37 1.0e-07 4.4e-06
KRT8P11 2.0 0.44 6.9e-05 0.00098
AC016383.2 1.9 0.35 0.0e+00 1.4e-06
AC093772.1 1.9 0.32 0.0e+00 7.3e-07
IGLVI-70 1.9 0.29 0.0e+00 6.4e-12
LINC02240 1.9 0.31 0.0e+00 4.4e-08
ST8SIA5 1.9 0.28 0.0e+00 2.2e-11
AC026785.2 1.8 0.35 4.0e-07 1e-05
LINC01189 1.8 0.30 0.0e+00 3.9e-08
FMO1 1.7 0.27 0.0e+00 2.6e-09
HCG4P8 1.7 0.28 0.0e+00 4.2e-09
7SK 1.5 0.23 0.0e+00 5e-11
GSTA7P 1.5 0.64 2.2e-03 0.016
IGLV1-44 1.5 0.11 0.0e+00 2.7e-38
IGLV9-49 1.5 0.15 0.0e+00 8.7e-22
POM121L6P 1.5 0.43 8.0e-04 0.0074
* Wald test p-values
Benjamini–Hochberg adjusted value

25 genes with largest positive log-fold change in experimental group

infected_vs_control: upregulated in infected
gene log2FoldChange lfc standard error pvalue* padj
KDM5D 2.2 0.43 0.0e+00 5e-08
BCORP1 2.0 0.63 4.2e-06 9.1e-05
EIF1AY 2.0 0.81 4.0e-05 0.00062
AC244213.1 1.9 0.57 1.1e-04 0.0015
PRKY 1.9 0.19 0.0e+00 5.8e-22
TMSB4Y 1.9 0.73 8.3e-04 0.0076
UTY 1.9 0.25 0.0e+00 1.1e-14
ZFY 1.9 0.24 0.0e+00 5.5e-16
KDM5DP1 1.8 0.58 4.8e-04 0.0049
USP9Y 1.7 0.17 0.0e+00 1e-24
AC010889.1 1.6 0.42 5.1e-06 0.00011
TLK2P1 1.6 0.42 1.3e-04 0.0016
NLGN4Y 1.5 0.40 4.0e-07 1.3e-05
LINC00278 1.4 0.11 0.0e+00 3.9e-35
ZFY-AS1 1.4 0.61 3.2e-03 0.022
AC096861.2 1.2 0.18 0.0e+00 1.3e-11
CCDC192 1.2 0.26 2.0e-07 5.7e-06
CR383656.13 1.2 0.29 2.6e-06 6e-05
CTBP2P6 1.2 0.23 0.0e+00 1.1e-07
FIGN 1.2 0.44 2.6e-04 0.0029
RPS27P25 1.2 0.50 5.5e-03 0.034
AC008391.1 1.1 0.29 2.3e-05 0.00039
AC097110.1 1.1 0.16 0.0e+00 2.7e-11
AC109129.1 1.1 0.24 1.0e-07 3.3e-06
AL139286.3 1.1 0.43 5.9e-04 0.0057
HMGN2P17 1.1 0.18 0.0e+00 5.9e-10
RAP1GAP 1.1 0.17 0.0e+00 6.1e-10
* Wald test p-values
Benjamini–Hochberg adjusted value

Expression of top class DE genes by class

Sorted by disease classification

Sorted by cluster

Sorted by hierarchical clustering

Expression of all top DE genes

Sorted by disease classification

Sorted by cluster

Sorted by hierarchical clustering

Volcano plot of gene expression

Expression of selected interferon-stimulated genes

Sorted by disease classification

Sorted by cluster

Sorted by hierarchical clustering

Expression of individual genes in the M1.2, M3.4, and M5.12 gene modules

Sorted by disease classification

Sorted by cluster

Sorted by hierarchical clustering

Sample Clustering

The eigenvales for the annotated Banchereau modules were used to calculate an adjacentcy matrix, which was in turn used to calculate the gap statistic to determine the optimal k-clusters.

Clustering and variation of samples in reduced dimensional space

PCA

PCA by disease classification

PCA by plate

PCA by ethnicity

PCA by K-means cluster

UMAP

UMAP by disease classification

UMAP by plate

UMAP by ethnicity

UMAP by K-means cluster

Module scores

SLE Interferon module scores

Sorted by disease classification

Sorted by cluster

Sorted by hierarchical clustering

SLE Inflammatory module scores

Sorted by disease classification

Sorted by cluster

Sorted by hierarchical clustering

Low-density granulocyte module scores

Sorted by disease classification

Sorted by cluster

Sorted by hierarchical clustering

SLE Modules with an annotated associated pathway

Sorted by disease classification

Sorted by cluster

Sorted by hierarchical clustering

All SLE modules

Sorted by disease classification

Sorted by cluster

Sorted by hierarchical clustering

Expression of the annotated Banchereau modules

By disease classification

By cluster

WGCNA

Expression similarity dendrogram

Expression of identified modules

By disease classification

By cluster

WGCNA eigenvalues

Sorted by disease classification

Sorted by cluster

Sorted by hierarchical clustering

Gene ontology GSEA of WGCNA modules

Use of WGCNA modules in classifying clusters.

The module eigengene scores were used to train a random forest model with repeated cross validation to predict cluster identity.

The model was trained with 75% of the dataset and tested on 25%.

Note: Subjects with LP were excluded due to the small population size.

## Confusion Matrix and Statistics
## 
##           Reference
## Prediction 1 2 3 4 5 6 7 8 9 10 11 12
##         1  1 1 0 0 0 0 1 0 0  0  0  2
##         2  0 0 0 0 0 0 1 0 0  0  0  0
##         3  0 0 1 0 0 1 0 0 1  0  0  0
##         4  0 0 1 1 1 0 0 3 1  1  2  0
##         5  0 0 1 2 5 0 0 0 1  1  3  0
##         6  1 0 2 1 0 1 2 0 0  1  0  3
##         7  0 0 0 0 0 1 0 0 0  1  1  1
##         8  0 0 1 0 0 1 0 0 0  2  2  0
##         9  0 0 0 1 0 0 0 0 1  0  0  0
##         10 0 0 1 0 0 0 0 0 1  0  0  0
##         11 0 0 0 4 1 1 0 1 0  0  2  0
##         12 3 1 4 0 0 3 3 0 1  0  0  1
## 
## Overall Statistics
##                                           
##                Accuracy : 0.1585          
##                  95% CI : (0.0872, 0.2558)
##     No Information Rate : 0.1341          
##     P-Value [Acc > NIR] : 0.3029          
##                                           
##                   Kappa : 0.075           
##                                           
##  Mcnemar's Test P-Value : NA              
## 
## Statistics by Class:
## 
##                      Class: 1 Class: 2 Class: 3 Class: 4 Class: 5 Class: 6 Class: 7 Class: 8 Class: 9 Class: 10 Class: 11 Class: 12
## Sensitivity           0.20000  0.00000  0.09091   0.1111  0.71429  0.12500  0.00000  0.00000  0.16667   0.00000   0.20000   0.14286
## Specificity           0.94805  0.98750  0.97183   0.8767  0.89333  0.86486  0.94667  0.92308  0.98684   0.97368   0.90278   0.80000
## Pos Pred Value        0.20000  0.00000  0.33333   0.1000  0.38462  0.09091  0.00000  0.00000  0.50000   0.00000   0.22222   0.06250
## Neg Pred Value        0.94805  0.97531  0.87342   0.8889  0.97101  0.90141  0.91026  0.94737  0.93750   0.92500   0.89041   0.90909
## Prevalence            0.06098  0.02439  0.13415   0.1098  0.08537  0.09756  0.08537  0.04878  0.07317   0.07317   0.12195   0.08537
## Detection Rate        0.01220  0.00000  0.01220   0.0122  0.06098  0.01220  0.00000  0.00000  0.01220   0.00000   0.02439   0.01220
## Detection Prevalence  0.06098  0.01220  0.03659   0.1220  0.15854  0.13415  0.04878  0.07317  0.02439   0.02439   0.10976   0.19512
## Balanced Accuracy     0.57403  0.49375  0.53137   0.4939  0.80381  0.49493  0.47333  0.46154  0.57675   0.48684   0.55139   0.47143

The relative importance of each eigengene in classification:

## parRF variable importance
## 
##   variables are sorted by maximum importance across the classes
##   only 20 most important variables shown (out of 30)
## 
##                       1        2       3        4       5        6        7        8        9        10      11      12
## MEdarkorange    -1.3952  1.89887  2.2487 -0.59569  0.1184  1.36791  2.57927  0.69672  0.49439  1.321858  2.7536  7.4600
## MEgreen          6.3469  0.18714 -0.1260  3.48698  3.2494 -0.31395  3.78028 -1.02585 -3.09892 -1.105285 -1.0086  0.3674
## MEcyan           1.5556  4.04098  0.4659  1.69556  4.7611  0.06799  4.71986  0.99135  0.94408  0.810165  2.5551  5.8870
## MEorange         3.4790  2.16043 -1.1680  0.68524  5.7286  0.39011  1.24308  1.27588 -0.43506  0.182313  2.7944  4.0107
## MEpink           5.3879  0.25300  0.2373  1.27497  2.8158  0.36091 -1.04704 -0.41999 -3.01515 -0.337741 -1.2650  1.0739
## MEwhite          2.1193  0.41613  1.9023 -0.69131 -1.0967  1.60930  1.27355  2.24060 -0.04428 -1.393684  5.0311 -0.1569
## MEskyblue        1.3933  0.61022  2.1430  1.06542  4.9282 -0.05518  0.37329 -0.57075  0.37477 -1.104002  3.6126  4.5060
## MEsalmon         4.7574  0.40597  1.0174  1.79920  1.2272  1.62260  2.34827  0.72911  0.53984  0.921454 -0.2533  0.2304
## MEmidnightblue   2.0613  2.90382 -0.6791  3.28034  4.7095  0.83694  2.22896 -1.26325 -1.38901  0.008223  3.7099  2.4345
## MEmagenta        3.4529  2.55145 -2.7483 -1.03871  3.7382  1.02076  4.17258 -0.41356 -1.30924 -1.058841 -0.2308  2.4149
## MEred            1.0351 -0.78341  0.2315 -0.34228  2.6509  4.06632  0.58416 -1.20773 -2.03843 -1.072346  3.4526 -0.2423
## MEsteelblue      0.8806  1.20487  1.6769  0.02673  2.7685  1.91906 -1.04167  0.57742 -0.32796 -1.610384  3.5512  1.5444
## MEyellow        -0.6784  1.53055  1.0733 -0.88162  1.3084 -0.55748 -0.04136  0.69660 -0.97973  1.140135  0.6219  3.5321
## MEroyalblue      1.6961  3.39865 -0.7374 -0.71418  0.1547  0.94313 -0.85468 -0.03278  0.21498  1.155358 -0.9200  0.6676
## MEpurple        -0.1744  0.07704 -0.2604 -1.47635  0.5152 -0.06305  0.89692  2.38490 -1.84506  0.101767  1.0979  3.2850
## MEdarkturquoise  0.3875  1.09676 -2.2895  0.23815 -0.8247 -0.04158  0.16045 -0.50402 -0.54100  0.595311  3.1920 -1.3016
## MEbrown          1.1030  0.28224 -0.5311  0.84570  2.5224  3.13080  1.38252  0.15978  0.51037 -0.302476  1.9038  2.5596
## MEtan           -1.4853  2.52392  1.6129 -0.39620 -1.0376  0.81379  0.60229 -1.39512 -0.62143  0.610480  0.9588  2.9527
## MEdarkgreen      2.2749 -1.09585  0.4798  1.48870  2.9515  1.21173 -0.77545  0.85379 -3.30784 -1.728997  0.9729  1.2572
## MEblack          0.5813  0.87160  0.3770 -0.29125  2.7848  0.46714  1.13752 -1.53809 -0.32256 -0.990952 -0.8510 -0.2955

Use of WGCNA modules in labeling disease class.

The module eigengene scores were used to train a random forest model with repeated cross validation to predict cluster identity.

The model was trained with 75% of the dataset and tested on 25%.

## Confusion Matrix and Statistics
## 
##           Reference
## Prediction control infected
##   control       29        1
##   infected       9       43
##                                           
##                Accuracy : 0.878           
##                  95% CI : (0.7871, 0.9399)
##     No Information Rate : 0.5366          
##     P-Value [Acc > NIR] : 3.957e-11       
##                                           
##                   Kappa : 0.7512          
##                                           
##  Mcnemar's Test P-Value : 0.02686         
##                                           
##             Sensitivity : 0.7632          
##             Specificity : 0.9773          
##          Pos Pred Value : 0.9667          
##          Neg Pred Value : 0.8269          
##              Prevalence : 0.4634          
##          Detection Rate : 0.3537          
##    Detection Prevalence : 0.3659          
##       Balanced Accuracy : 0.8702          
##                                           
##        'Positive' Class : control         
## 

The relative importance of each eigengene in classification:

## parRF variable importance
## 
##   only 20 most important variables shown (out of 30)
## 
##                Overall
## MEskyblue       49.000
## MEsteelblue     13.434
## MElightyellow    9.624
## MEwhite          7.969
## MEbrown          3.920
## MEroyalblue      3.618
## MEsaddlebrown    3.490
## MElightgreen     2.640
## MEtan            2.217
## MEred            2.203
## MEcyan           2.025
## MEdarkorange     1.948
## MEpurple         1.946
## MEgrey60         1.900
## MEblack          1.820
## MEmidnightblue   1.812
## MEblue           1.701
## MEdarkred        1.420
## MEmagenta        1.234
## MElightcyan      1.130

Use of module modules in classifying clusters.

The module eigengene scores were used to train a random forest model with repeated cross validation to predict cluster identity.

The model was trained with 75% of the dataset and tested on 25%.

## Confusion Matrix and Statistics
## 
##           Reference
## Prediction 1 2 3 4 5 6 7 8 9 10 11 12
##         1  1 0 1 0 0 1 0 0 0  0  1  1
##         2  0 1 0 0 0 0 0 0 0  0  0  0
##         3  0 0 0 0 0 2 0 1 3  0  1  1
##         4  1 0 2 0 0 1 0 1 1  0  0  0
##         5  0 0 0 2 5 0 0 4 0  1  6  0
##         6  0 0 2 1 0 1 1 0 0  1  0  1
##         7  1 1 1 0 0 0 0 0 0  1  0  4
##         8  0 0 0 0 0 0 0 0 0  0  0  0
##         9  0 0 0 2 0 0 0 0 0  1  1  0
##         10 0 0 0 0 0 0 0 0 0  0  0  0
##         11 0 0 1 3 4 0 1 6 1  3  3  0
##         12 0 0 0 1 0 1 1 0 0  1  0  0
## 
## Overall Statistics
##                                           
##                Accuracy : 0.1325          
##                  95% CI : (0.0681, 0.2248)
##     No Information Rate : 0.1446          
##     P-Value [Acc > NIR] : 0.6694          
##                                           
##                   Kappa : 0.0395          
##                                           
##  Mcnemar's Test P-Value : NA              
## 
## Statistics by Class:
## 
##                      Class: 1 Class: 2 Class: 3 Class: 4 Class: 5 Class: 6 Class: 7 Class: 8 Class: 9 Class: 10 Class: 11 Class: 12
## Sensitivity           0.33333  0.50000  0.00000  0.00000  0.55556  0.16667  0.00000   0.0000  0.00000   0.00000   0.25000   0.00000
## Specificity           0.95000  1.00000  0.89474  0.91892  0.82432  0.92208  0.90000   1.0000  0.94872   1.00000   0.73239   0.94737
## Pos Pred Value        0.20000  1.00000  0.00000  0.00000  0.27778  0.14286  0.00000      NaN  0.00000       NaN   0.13636   0.00000
## Neg Pred Value        0.97436  0.98780  0.90667  0.88312  0.93846  0.93421  0.96000   0.8554  0.93671   0.90361   0.85246   0.91139
## Prevalence            0.03614  0.02410  0.08434  0.10843  0.10843  0.07229  0.03614   0.1446  0.06024   0.09639   0.14458   0.08434
## Detection Rate        0.01205  0.01205  0.00000  0.00000  0.06024  0.01205  0.00000   0.0000  0.00000   0.00000   0.03614   0.00000
## Detection Prevalence  0.06024  0.01205  0.09639  0.07229  0.21687  0.08434  0.09639   0.0000  0.04819   0.00000   0.26506   0.04819
## Balanced Accuracy     0.64167  0.75000  0.44737  0.45946  0.68994  0.54437  0.45000   0.5000  0.47436   0.50000   0.49120   0.47368

The relative importance of each eigengene in classification:

## parRF variable importance
## 
##   variables are sorted by maximum importance across the classes
##   only 20 most important variables shown (out of 260)
## 
##              1       2        3       4      5       6        7       8       9      10        11       12
## M8.73   6.6793  1.8735 -0.24795  3.1531 3.4482 -0.7082  1.93138 -0.2403 -1.5476 -0.9622 -1.749856 -0.81022
## M9.3   -1.2981 -1.0112  2.35450  3.0177 5.2362  1.2023  2.11434 -1.6746 -0.1239 -0.1487  2.990503  1.18935
## M1.2    1.3435  1.6691 -0.53550  1.9847 4.7295 -0.1790  1.97096 -0.5557  1.4660 -1.0010  0.959979  1.04364
## M8.9    4.0834  0.7813  2.59897  4.6416 3.3387 -1.6693  1.63225 -1.9281 -1.9441  0.7893  3.262826 -0.06088
## M9.46   2.1446  1.3894 -1.50550  2.2101 3.8952  0.6430  1.66489 -1.6358 -1.4446  0.1105  0.002465  0.35608
## M8.3    1.3214  1.2669  1.97169  1.6291 2.9199  0.7761  0.89539  0.3209 -2.4928 -2.4663  3.860012  1.68357
## M8.53  -2.7434  1.2171  0.01224  1.2811 2.8302 -2.2821  3.64189  0.8152 -1.6527 -0.3957  3.312052  2.81689
## M7.35   1.8782  0.0000 -0.74860  0.1429 0.5935  0.7424  0.01569 -0.2315 -0.1086 -0.1280  3.626360  0.76324
## M7.32   2.9070  0.0000  0.05742  1.3509 0.3823  3.5991  1.07274 -0.6475  0.4066  1.1046  0.358513 -0.30210
## M4.8    1.7370  3.4818  1.55086  1.9600 0.4727  0.7437 -0.64545 -1.0010 -0.2665  0.5185  0.584613 -0.44510
## M9.37   0.8873  1.5110 -0.67573  1.5960 3.4731 -0.7560  0.40651 -1.7371 -1.5640  1.0319  0.232192 -2.36505
## M8.42   0.9748  1.4171  3.12432  2.2979 3.4479  1.2490  0.97418 -1.5447 -1.1969 -0.2515  1.231625  0.10545
## M5.9    3.4165  1.0010  0.23923  2.0566 1.0024  1.0742  2.32143  0.9070 -0.4159 -0.6738  0.369391 -0.03494
## M8.28   2.5649  0.1280  3.14703  0.9509 2.2879  1.7754  0.09200 -0.1176 -2.2778  0.5752  3.218694  0.23017
## M8.105  3.1713  0.0000  1.32364  0.7301 2.0592  0.8571  0.27107 -0.1174 -0.5687 -0.8710 -0.324682 -1.96532
## M8.82   1.4083 -1.0010  1.00100  0.3491 3.1305  0.5594  2.06440 -0.8122 -1.0996  1.0010 -1.473120  1.00100
## M7.13  -2.5093 -0.4473  1.89518 -0.1068 3.1141  1.1832  0.44730 -0.8461  0.5645  1.0010  0.564208  0.06762
## M8.95   1.5551 -1.0010  1.01522  1.0513 3.0750  0.8043 -0.35305 -1.5749 -0.3166 -1.1729 -0.150149  0.32883
## M9.25  -1.2565  0.4890  2.63519 -0.0558 0.9286  0.4289 -0.28561 -1.9856  1.1310 -1.3178  3.068939  0.58601
## M8.6    0.9923  0.3847  0.31963  0.3966 0.8528  1.2223 -0.60246 -0.4696 -1.0438  2.9758  2.584557 -1.01800

Use of module modules in labeling disease class.

The module eigengene scores were used to train a random forest model with repeated cross validation to predict cluster identity.

The model was trained with 75% of the dataset and tested on 25%.

## Confusion Matrix and Statistics
## 
##           Reference
## Prediction control infected
##   control       26        4
##   infected      12       40
##                                           
##                Accuracy : 0.8049          
##                  95% CI : (0.7026, 0.8842)
##     No Information Rate : 0.5366          
##     P-Value [Acc > NIR] : 3.701e-07       
##                                           
##                   Kappa : 0.6019          
##                                           
##  Mcnemar's Test P-Value : 0.08012         
##                                           
##             Sensitivity : 0.6842          
##             Specificity : 0.9091          
##          Pos Pred Value : 0.8667          
##          Neg Pred Value : 0.7692          
##              Prevalence : 0.4634          
##          Detection Rate : 0.3171          
##    Detection Prevalence : 0.3659          
##       Balanced Accuracy : 0.7967          
##                                           
##        'Positive' Class : control         
## 

The relative importance of each eigengene in classification:

## parRF variable importance
## 
##   only 20 most important variables shown (out of 260)
## 
##       Importance
## M5.15     25.344
## M1.2      18.188
## M7.26      8.437
## M4.11      7.449
## M8.56      7.384
## M3.4       4.417
## M9.32      4.231
## M9.41      4.076
## M9.11      3.728
## M8.15      3.582
## M1.1       3.470
## M8.53      3.418
## M8.16      3.254
## M8.59      2.933
## M8.30      2.684
## M7.13      2.543
## M8.63      2.416
## M8.95      2.292
## M9.52      2.169
## M2.3       2.115
## ─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
##  setting  value                       
##  version  R version 4.0.4 (2021-02-15)
##  os       Ubuntu 20.04 LTS            
##  system   x86_64, linux-gnu           
##  ui       X11                         
##  language (EN)                        
##  collate  en_US.UTF-8                 
##  ctype    en_US.UTF-8                 
##  tz       Etc/UTC                     
##  date     2021-03-18                  
## 
## ─ Packages ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
##  package              * version    date       lib source                                   
##  abind                  1.4-5      2016-07-21 [1] RSPM (R 4.0.4)                           
##  annotate               1.68.0     2020-10-27 [1] Bioconductor                             
##  AnnotationDbi          1.52.0     2020-10-27 [1] RSPM (R 4.0.4)                           
##  assertthat             0.2.1      2019-03-21 [1] RSPM (R 4.0.3)                           
##  backports              1.2.1      2020-12-09 [1] RSPM (R 4.0.4)                           
##  base64enc              0.1-3      2015-07-28 [1] RSPM (R 4.0.3)                           
##  base64url              1.4        2018-05-14 [1] RSPM (R 4.0.4)                           
##  Biobase              * 2.50.0     2020-10-27 [1] RSPM (R 4.0.4)                           
##  BiocGenerics         * 0.36.0     2020-10-27 [1] RSPM (R 4.0.4)                           
##  BiocManager            1.30.10    2019-11-16 [1] CRAN (R 4.0.4)                           
##  BiocParallel         * 1.24.1     2020-11-06 [1] RSPM (R 4.0.4)                           
##  bit                    4.0.4      2020-08-04 [1] RSPM (R 4.0.3)                           
##  bit64                  4.0.5      2020-08-30 [1] RSPM (R 4.0.3)                           
##  bitops                 1.0-6      2013-08-17 [1] RSPM (R 4.0.4)                           
##  blob                   1.2.1      2020-01-20 [1] RSPM (R 4.0.4)                           
##  broom                * 0.7.5      2021-02-19 [1] RSPM (R 4.0.4)                           
##  bslib                  0.2.4      2021-01-25 [1] RSPM (R 4.0.4)                           
##  cachem                 1.0.4      2021-02-13 [1] RSPM (R 4.0.3)                           
##  car                    3.0-10     2020-09-29 [1] RSPM (R 4.0.4)                           
##  carData                3.0-4      2020-05-22 [1] RSPM (R 4.0.4)                           
##  caret                * 6.0-86     2020-03-20 [1] RSPM (R 4.0.3)                           
##  cellranger             1.1.0      2016-07-27 [1] RSPM (R 4.0.4)                           
##  checkmate              2.0.0      2020-02-06 [1] RSPM (R 4.0.4)                           
##  class                  7.3-18     2021-01-24 [2] CRAN (R 4.0.4)                           
##  cli                    2.3.1      2021-02-23 [1] RSPM (R 4.0.3)                           
##  cluster              * 2.1.1      2021-02-14 [1] RSPM (R 4.0.3)                           
##  clusterProfiler      * 3.18.1     2021-02-09 [1] Bioconductor                             
##  codetools              0.2-18     2020-11-04 [2] CRAN (R 4.0.4)                           
##  colorspace             2.0-0      2020-11-11 [1] RSPM (R 4.0.4)                           
##  corrplot             * 0.84       2017-10-16 [1] RSPM (R 4.0.4)                           
##  cowplot              * 1.1.1      2020-12-30 [1] RSPM (R 4.0.4)                           
##  crayon                 1.4.1      2021-02-08 [1] RSPM (R 4.0.3)                           
##  crosstalk              1.1.1      2021-01-12 [1] RSPM (R 4.0.3)                           
##  curl                   4.3        2019-12-02 [1] RSPM (R 4.0.3)                           
##  data.table           * 1.14.0     2021-02-21 [1] RSPM (R 4.0.4)                           
##  DBI                    1.1.1      2021-01-15 [1] RSPM (R 4.0.4)                           
##  dbplyr                 2.1.0      2021-02-03 [1] RSPM (R 4.0.4)                           
##  DelayedArray           0.16.2     2021-02-26 [1] RSPM (R 4.0.4)                           
##  DESeq2               * 1.30.1     2021-02-19 [1] RSPM (R 4.0.4)                           
##  dials                * 0.0.9      2020-09-16 [1] RSPM (R 4.0.3)                           
##  DiceDesign             1.9        2021-02-13 [1] RSPM (R 4.0.3)                           
##  digest                 0.6.27     2020-10-24 [1] RSPM (R 4.0.3)                           
##  DO.db                  2.9        2021-03-13 [1] RSPM (R 4.0.4)                           
##  doParallel             1.0.16     2020-10-16 [1] RSPM (R 4.0.4)                           
##  DOSE                   3.16.0     2020-10-27 [1] RSPM (R 4.0.4)                           
##  downloader             0.4        2015-07-09 [1] RSPM (R 4.0.4)                           
##  dplyr                * 1.0.5      2021-03-05 [1] RSPM (R 4.0.4)                           
##  drake                * 7.13.1     2021-02-03 [1] RSPM (R 4.0.4)                           
##  DT                     0.17       2021-01-06 [1] RSPM (R 4.0.3)                           
##  dynamicTreeCut       * 1.63-1     2016-03-11 [1] RSPM (R 4.0.4)                           
##  e1071                  1.7-5      2021-03-15 [1] RSPM (R 4.0.4)                           
##  edgeR                  3.32.1     2021-01-14 [1] RSPM (R 4.0.4)                           
##  ellipsis               0.3.1      2020-05-15 [1] RSPM (R 4.0.3)                           
##  enrichplot             1.10.2     2021-01-28 [1] RSPM (R 4.0.4)                           
##  evaluate               0.14       2019-05-28 [1] RSPM (R 4.0.3)                           
##  factoextra           * 1.0.7      2020-04-01 [1] RSPM (R 4.0.3)                           
##  fansi                  0.4.2      2021-01-15 [1] RSPM (R 4.0.3)                           
##  farver                 2.1.0      2021-02-28 [1] RSPM (R 4.0.4)                           
##  fastcluster          * 1.1.25     2018-06-07 [1] RSPM (R 4.0.4)                           
##  fastmap                1.1.0      2021-01-25 [1] RSPM (R 4.0.3)                           
##  fastmatch              1.1-0      2017-01-28 [1] RSPM (R 4.0.4)                           
##  fgsea                  1.16.0     2020-10-27 [1] RSPM (R 4.0.4)                           
##  filelock               1.0.2      2018-10-05 [1] RSPM (R 4.0.4)                           
##  flextable            * 0.6.4      2021-03-10 [1] RSPM (R 4.0.3)                           
##  FNN                    1.1.3      2019-02-15 [1] RSPM (R 4.0.4)                           
##  forcats              * 0.5.1      2021-01-27 [1] RSPM (R 4.0.4)                           
##  foreach                1.5.1      2020-10-15 [1] RSPM (R 4.0.4)                           
##  foreign                0.8-81     2020-12-22 [2] CRAN (R 4.0.4)                           
##  formattable          * 0.2.1      2021-01-07 [1] RSPM (R 4.0.4)                           
##  Formula                1.2-4      2020-10-16 [1] RSPM (R 4.0.4)                           
##  fs                     1.5.0      2020-07-31 [1] RSPM (R 4.0.3)                           
##  furrr                * 0.2.2      2021-01-29 [1] RSPM (R 4.0.4)                           
##  future               * 1.21.0     2020-12-10 [1] RSPM (R 4.0.4)                           
##  gdtools                0.2.3      2021-01-06 [1] RSPM (R 4.0.3)                           
##  genefilter           * 1.72.1     2021-01-21 [1] RSPM (R 4.0.4)                           
##  geneplotter            1.68.0     2020-10-27 [1] RSPM (R 4.0.4)                           
##  generics               0.1.0      2020-10-31 [1] RSPM (R 4.0.4)                           
##  GenomeInfoDb         * 1.26.4     2021-03-10 [1] Bioconductor                             
##  GenomeInfoDbData       1.2.4      2021-03-13 [1] RSPM (R 4.0.4)                           
##  GenomicRanges        * 1.42.0     2020-10-27 [1] RSPM (R 4.0.4)                           
##  ggfittext              0.9.1      2021-01-30 [1] RSPM (R 4.0.4)                           
##  ggforce              * 0.3.2.9000 2021-03-17 [1] Github (thomasp85/ggforce@1f17eb3)       
##  ggplot2              * 3.3.3      2020-12-30 [1] RSPM (R 4.0.4)                           
##  ggplotify            * 0.0.5      2020-03-12 [1] RSPM (R 4.0.0)                           
##  ggpubr               * 0.4.0      2020-06-27 [1] RSPM (R 4.0.4)                           
##  ggradar              * 0.2        2021-03-16 [1] Github (ricardo-bion/ggradar@63e5cef)    
##  ggraph                 2.0.5      2021-02-23 [1] RSPM (R 4.0.4)                           
##  ggrepel              * 0.9.1      2021-01-15 [1] RSPM (R 4.0.3)                           
##  ggsignif               0.6.1      2021-02-23 [1] RSPM (R 4.0.4)                           
##  ggtext               * 0.1.1      2020-12-17 [1] RSPM (R 4.0.3)                           
##  globals                0.14.0     2020-11-22 [1] RSPM (R 4.0.4)                           
##  glue                   1.4.2      2020-08-27 [1] RSPM (R 4.0.3)                           
##  GO.db                  3.12.1     2021-03-13 [1] RSPM (R 4.0.4)                           
##  GOSemSim               2.16.1     2020-10-29 [1] RSPM (R 4.0.4)                           
##  gower                  0.2.2      2020-06-23 [1] RSPM (R 4.0.3)                           
##  GPfit                  1.0-8      2019-02-08 [1] RSPM (R 4.0.3)                           
##  graphlayouts           0.7.1      2020-10-26 [1] RSPM (R 4.0.4)                           
##  gridBase               0.4-7      2014-02-24 [1] RSPM (R 4.0.4)                           
##  gridExtra              2.3        2017-09-09 [1] RSPM (R 4.0.4)                           
##  gridGraphics           0.5-1      2020-12-13 [1] RSPM (R 4.0.3)                           
##  gridtext               0.1.4      2020-12-10 [1] RSPM (R 4.0.4)                           
##  gtable                 0.3.0      2019-03-25 [1] RSPM (R 4.0.4)                           
##  gtools               * 3.8.2      2020-03-31 [1] RSPM (R 4.0.4)                           
##  haven                  2.3.1      2020-06-01 [1] RSPM (R 4.0.4)                           
##  here                 * 1.0.1      2020-12-13 [1] RSPM (R 4.0.4)                           
##  HGNChelper           * 0.8.1      2019-10-24 [1] RSPM (R 4.0.0)                           
##  highr                  0.8        2019-03-20 [1] RSPM (R 4.0.3)                           
##  Hmisc                  4.5-0      2021-02-28 [1] RSPM (R 4.0.4)                           
##  hms                    1.0.0      2021-01-13 [1] RSPM (R 4.0.4)                           
##  htmlTable              2.1.0      2020-09-16 [1] RSPM (R 4.0.4)                           
##  htmltools              0.5.1.1    2021-01-22 [1] RSPM (R 4.0.3)                           
##  htmlwidgets            1.5.3      2020-12-10 [1] RSPM (R 4.0.3)                           
##  httr                   1.4.2      2020-07-20 [1] RSPM (R 4.0.3)                           
##  igraph                 1.2.6      2020-10-06 [1] RSPM (R 4.0.4)                           
##  import                 1.2.0      2020-09-24 [1] RSPM (R 4.0.2)                           
##  impute                 1.64.0     2020-10-27 [1] RSPM (R 4.0.4)                           
##  infer                * 0.5.4      2021-01-13 [1] RSPM (R 4.0.3)                           
##  inspectdf            * 0.0.10     2021-02-20 [1] RSPM (R 4.0.4)                           
##  ipred                  0.9-11     2021-03-12 [1] RSPM (R 4.0.3)                           
##  IRanges              * 2.24.1     2020-12-12 [1] RSPM (R 4.0.4)                           
##  irlba                * 2.3.3      2019-02-05 [1] RSPM (R 4.0.3)                           
##  iterators              1.0.13     2020-10-15 [1] RSPM (R 4.0.4)                           
##  janitor              * 2.1.0      2021-01-05 [1] RSPM (R 4.0.4)                           
##  jpeg                   0.1-8.1    2019-10-24 [1] RSPM (R 4.0.4)                           
##  jquerylib              0.1.3      2020-12-17 [1] RSPM (R 4.0.4)                           
##  jsonlite               1.7.2      2020-12-09 [1] RSPM (R 4.0.3)                           
##  kableExtra           * 1.3.4      2021-02-20 [1] RSPM (R 4.0.4)                           
##  knitr                * 1.31       2021-01-27 [1] RSPM (R 4.0.3)                           
##  labeling               0.4.2      2020-10-20 [1] RSPM (R 4.0.4)                           
##  lattice              * 0.20-41    2020-04-02 [2] CRAN (R 4.0.4)                           
##  latticeExtra           0.6-29     2019-12-19 [1] RSPM (R 4.0.4)                           
##  lava                   1.6.9      2021-03-11 [1] RSPM (R 4.0.3)                           
##  lazyeval               0.2.2      2019-03-15 [1] RSPM (R 4.0.3)                           
##  lhs                    1.1.1      2020-10-05 [1] RSPM (R 4.0.3)                           
##  lifecycle              1.0.0      2021-02-15 [1] RSPM (R 4.0.3)                           
##  limma                  3.46.0     2020-10-27 [1] RSPM (R 4.0.4)                           
##  listenv                0.8.0      2019-12-05 [1] RSPM (R 4.0.4)                           
##  locfit                 1.5-9.4    2020-03-25 [1] RSPM (R 4.0.4)                           
##  lubridate              1.7.10     2021-02-26 [1] RSPM (R 4.0.4)                           
##  magrittr             * 2.0.1      2020-11-17 [1] RSPM (R 4.0.3)                           
##  markdown               1.1        2019-08-07 [1] RSPM (R 4.0.3)                           
##  MASS                   7.3-53.1   2021-02-12 [2] RSPM (R 4.0.3)                           
##  Matrix               * 1.3-2      2021-01-06 [2] CRAN (R 4.0.4)                           
##  MatrixGenerics       * 1.2.1      2021-01-30 [1] RSPM (R 4.0.4)                           
##  matrixStats          * 0.58.0     2021-01-29 [1] RSPM (R 4.0.4)                           
##  memoise                2.0.0      2021-01-26 [1] RSPM (R 4.0.3)                           
##  mgcv                 * 1.8-34     2021-02-16 [2] RSPM (R 4.0.3)                           
##  modeldata            * 0.1.0      2020-10-22 [1] RSPM (R 4.0.3)                           
##  ModelMetrics           1.2.2.2    2020-03-17 [1] RSPM (R 4.0.3)                           
##  modelr                 0.1.8      2020-05-19 [1] RSPM (R 4.0.4)                           
##  moduleScoreR         * 0.0.0.9200 2021-03-13 [1] Github (milescsmith/moduleScoreR@e6db70f)
##  munsell                0.5.0      2018-06-12 [1] RSPM (R 4.0.4)                           
##  nlme                 * 3.1-152    2021-02-04 [2] CRAN (R 4.0.4)                           
##  NMF                    0.23.0     2020-08-01 [1] RSPM (R 4.0.4)                           
##  nnet                   7.3-15     2021-01-24 [2] CRAN (R 4.0.4)                           
##  oaColors             * 0.0.4      2015-11-30 [1] RSPM (R 4.0.0)                           
##  officer                0.3.17     2021-03-05 [1] RSPM (R 4.0.3)                           
##  openxlsx               4.2.3      2020-10-27 [1] RSPM (R 4.0.4)                           
##  paletteer            * 1.3.0      2021-01-06 [1] RSPM (R 4.0.4)                           
##  parallelDist           0.2.4      2018-12-12 [1] RSPM (R 4.0.4)                           
##  parallelly             1.24.0     2021-03-14 [1] RSPM (R 4.0.3)                           
##  parsnip              * 0.1.5      2021-01-19 [1] RSPM (R 4.0.3)                           
##  pheatmap             * 1.0.12     2019-01-04 [1] RSPM (R 4.0.4)                           
##  pillar                 1.5.1      2021-03-05 [1] RSPM (R 4.0.3)                           
##  pkgconfig              2.0.3      2019-09-22 [1] RSPM (R 4.0.3)                           
##  pkgmaker               0.32.2     2020-10-20 [1] RSPM (R 4.0.4)                           
##  plotly               * 4.9.3      2021-01-10 [1] RSPM (R 4.0.4)                           
##  plyr                   1.8.6      2020-03-03 [1] RSPM (R 4.0.4)                           
##  png                    0.1-7      2013-12-03 [1] RSPM (R 4.0.4)                           
##  polyclip               1.10-0     2019-03-14 [1] RSPM (R 4.0.4)                           
##  preprocessCore         1.52.1     2021-01-08 [1] RSPM (R 4.0.4)                           
##  prettyunits            1.1.1      2020-01-24 [1] RSPM (R 4.0.3)                           
##  prismatic              1.0.0      2021-01-05 [1] RSPM (R 4.0.4)                           
##  pROC                   1.17.0.1   2021-01-13 [1] RSPM (R 4.0.3)                           
##  prodlim                2019.11.13 2019-11-17 [1] RSPM (R 4.0.3)                           
##  progress               1.2.2      2019-05-16 [1] RSPM (R 4.0.4)                           
##  proxy                  0.4-25     2021-03-05 [1] RSPM (R 4.0.3)                           
##  purrr                * 0.3.4      2020-04-17 [1] RSPM (R 4.0.3)                           
##  qvalue                 2.22.0     2020-10-27 [1] RSPM (R 4.0.4)                           
##  R6                     2.5.0      2020-10-28 [1] RSPM (R 4.0.3)                           
##  randomForest         * 4.6-14     2018-03-25 [1] RSPM (R 4.0.3)                           
##  RColorBrewer         * 1.1-2      2014-12-07 [1] RSPM (R 4.0.3)                           
##  Rcpp                   1.0.6      2021-01-15 [1] RSPM (R 4.0.4)                           
##  RcppParallel           5.0.3      2021-02-24 [1] RSPM (R 4.0.4)                           
##  RCurl                  1.98-1.2   2020-04-18 [1] RSPM (R 4.0.4)                           
##  readr                * 1.4.0      2020-10-05 [1] RSPM (R 4.0.4)                           
##  readxl               * 1.3.1      2019-03-13 [1] RSPM (R 4.0.3)                           
##  recipes              * 0.1.15     2020-11-11 [1] RSPM (R 4.0.3)                           
##  registry               0.5-1      2019-03-05 [1] RSPM (R 4.0.4)                           
##  rematch2               2.1.2      2020-05-01 [1] RSPM (R 4.0.3)                           
##  reprex                 1.0.0      2021-01-27 [1] RSPM (R 4.0.4)                           
##  reshape2               1.4.4      2020-04-09 [1] RSPM (R 4.0.4)                           
##  reticulate             1.18       2020-10-25 [1] RSPM (R 4.0.4)                           
##  rio                    0.5.26     2021-03-01 [1] RSPM (R 4.0.4)                           
##  rlang                * 0.4.10     2020-12-30 [1] RSPM (R 4.0.3)                           
##  rmarkdown            * 2.7        2021-02-19 [1] RSPM (R 4.0.4)                           
##  rngtools               1.5        2020-01-23 [1] RSPM (R 4.0.4)                           
##  rpart                  4.1-15     2019-04-12 [2] CRAN (R 4.0.4)                           
##  rprojroot              2.0.2      2020-11-15 [1] RSPM (R 4.0.3)                           
##  rsample              * 0.0.9      2021-02-17 [1] RSPM (R 4.0.3)                           
##  RSpectra               0.16-0     2019-12-01 [1] RSPM (R 4.0.4)                           
##  RSQLite                2.2.4      2021-03-12 [1] RSPM (R 4.0.3)                           
##  rstatix              * 0.7.0      2021-02-13 [1] RSPM (R 4.0.4)                           
##  rstudioapi             0.13       2020-11-12 [1] RSPM (R 4.0.3)                           
##  rsvd                   1.0.3      2020-02-17 [1] RSPM (R 4.0.4)                           
##  rvcheck                0.1.8      2020-03-01 [1] RSPM (R 4.0.4)                           
##  rvest                  1.0.0      2021-03-09 [1] RSPM (R 4.0.4)                           
##  S4Vectors            * 0.28.1     2020-12-09 [1] RSPM (R 4.0.4)                           
##  sass                   0.3.1      2021-01-24 [1] RSPM (R 4.0.4)                           
##  scales               * 1.1.1      2020-05-11 [1] RSPM (R 4.0.3)                           
##  scatterpie             0.1.5      2020-09-09 [1] RSPM (R 4.0.4)                           
##  sessioninfo            1.1.1      2018-11-05 [1] RSPM (R 4.0.3)                           
##  shadowtext             0.0.7      2019-11-06 [1] RSPM (R 4.0.4)                           
##  snakecase              0.11.0     2019-05-25 [1] RSPM (R 4.0.4)                           
##  snow                   0.4-3      2018-09-14 [1] RSPM (R 4.0.4)                           
##  storr                  1.2.5      2020-12-01 [1] RSPM (R 4.0.4)                           
##  stringi                1.5.3      2020-09-09 [1] RSPM (R 4.0.3)                           
##  stringr              * 1.4.0      2019-02-10 [1] RSPM (R 4.0.3)                           
##  SummarizedExperiment * 1.20.0     2020-10-27 [1] RSPM (R 4.0.4)                           
##  survival               3.2-7      2020-09-28 [2] CRAN (R 4.0.4)                           
##  sva                  * 3.38.0     2020-10-27 [1] Bioconductor                             
##  svglite                2.0.0      2021-02-20 [1] RSPM (R 4.0.4)                           
##  systemfonts            1.0.1      2021-02-09 [1] RSPM (R 4.0.4)                           
##  tibble               * 3.1.0      2021-02-25 [1] RSPM (R 4.0.3)                           
##  tidygraph              1.2.0      2020-05-12 [1] RSPM (R 4.0.4)                           
##  tidymodels           * 0.1.2      2020-11-22 [1] RSPM (R 4.0.3)                           
##  tidyr                * 1.1.3      2021-03-03 [1] RSPM (R 4.0.4)                           
##  tidyselect             1.1.0      2020-05-11 [1] RSPM (R 4.0.4)                           
##  tidyverse            * 1.3.0      2019-11-21 [1] RSPM (R 4.0.4)                           
##  timeDate               3043.102   2018-02-21 [1] RSPM (R 4.0.3)                           
##  tune                 * 0.1.3      2021-02-28 [1] RSPM (R 4.0.3)                           
##  tweenr                 1.0.1      2018-12-14 [1] RSPM (R 4.0.4)                           
##  tximport             * 1.18.0     2020-10-27 [1] RSPM (R 4.0.4)                           
##  txtq                   0.2.3      2020-06-23 [1] RSPM (R 4.0.4)                           
##  utf8                   1.2.1      2021-03-12 [1] RSPM (R 4.0.3)                           
##  uuid                   0.1-4      2020-02-26 [1] RSPM (R 4.0.3)                           
##  uwot                 * 0.1.10     2020-12-15 [1] RSPM (R 4.0.4)                           
##  vctrs                  0.3.6      2020-12-17 [1] RSPM (R 4.0.3)                           
##  viridis              * 0.5.1      2018-03-29 [1] RSPM (R 4.0.3)                           
##  viridisLite          * 0.3.0      2018-02-01 [1] RSPM (R 4.0.4)                           
##  webshot                0.5.2      2019-11-22 [1] RSPM (R 4.0.4)                           
##  WGCNA                * 1.70-3     2021-02-28 [1] RSPM (R 4.0.4)                           
##  withr                  2.4.1      2021-01-26 [1] RSPM (R 4.0.3)                           
##  workflows            * 0.2.2      2021-03-10 [1] RSPM (R 4.0.3)                           
##  xfun                   0.22       2021-03-11 [1] RSPM (R 4.0.3)                           
##  XML                    3.99-0.5   2020-07-23 [1] RSPM (R 4.0.4)                           
##  xml2                   1.3.2      2020-04-23 [1] RSPM (R 4.0.3)                           
##  xtable                 1.8-4      2019-04-21 [1] RSPM (R 4.0.4)                           
##  XVector                0.30.0     2020-10-27 [1] RSPM (R 4.0.4)                           
##  yaml                   2.2.1      2020-02-01 [1] RSPM (R 4.0.3)                           
##  yardstick            * 0.0.7      2020-07-13 [1] RSPM (R 4.0.3)                           
##  zip                    2.1.1      2020-08-27 [1] RSPM (R 4.0.3)                           
##  zlibbioc               1.36.0     2020-10-27 [1] RSPM (R 4.0.4)                           
## 
## [1] /usr/local/lib/R/site-library
## [2] /usr/local/lib/R/library